{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4bdd9a1c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T13:59:54.996096Z",
     "start_time": "2023-05-04T13:59:53.235284Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'cuda'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "from torch import nn\n",
    "import torch.nn.functional as F\n",
    "import transformers\n",
    "from transformers import AutoTokenizer, AutoConfig, AutoModel\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "from IPython.display import Image\n",
    "# default: 100\n",
    "mpl.rcParams['figure.dpi'] = 150\n",
    "device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
    "device"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daeea5cb",
   "metadata": {},
   "source": [
    "## summary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb38164a",
   "metadata": {},
   "source": [
    "- transformer-based language model\n",
    "    - 目前最核心的一个能力：text generation，尤其对于 gpt 而言；\n",
    "- openai gpt2\n",
    "    - https://openai.com/research/better-language-models\n",
    "- 预训练之后，被 prompt（context）激活的广泛的能力"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4a9ef312",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:01:13.541152Z",
     "start_time": "2023-05-04T14:01:13.528297Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 2,
     "metadata": {
      "image/png": {
       "width": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('../imgs/pretrain.png', width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "470d71b1",
   "metadata": {},
   "source": [
    "### pretrained model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cadf6869",
   "metadata": {},
   "source": [
    "- on English language\n",
    "- causal language modeling (CLM) objective. (多分类问题）\n",
    "- Language Models are Unsupervised Multitask Learners\n",
    "    - https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76920ceb",
   "metadata": {},
   "source": [
    "### decoding strategies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bd0c338",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-03T14:19:27.750077Z",
     "start_time": "2023-05-03T14:19:27.740847Z"
    }
   },
   "source": [
    "- converting the model’s probabilistic output（vocab size classification） to text\n",
    "    - iteratively，意味着更多的计算量\n",
    "    - quality & diversity\n",
    "- greedy search decoding：搜狗输入法，每次都用top1的候选\n",
    "- beam search decoding\n",
    "- sampling methods\n",
    "- top-k & nucleus sampling"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f0b321d",
   "metadata": {},
   "source": [
    "- (autoregressive or causal) language models\n",
    "\n",
    "- $\\textbf{x}=x_1,x_2,\\cdots,x_k. \\textbf{y}=y_1,y_2,\\cdots,y_t.$\n",
    "    - chain rule of probability to factorize it as a product of conditional probabilities\n",
    "$$\n",
    "\\begin{split}\n",
    "P(\\textbf{y}|\\textbf{x})&=P(y_1,y_2,\\cdots,y_t|\\textbf{x})\\\\\n",
    "&=\\Pi_{t=1}^Np(y_t|y_{\\lt t}, \\textbf{x})\\quad (y_{\\lt t}=y_{1,2,\\cdots,t-1})\n",
    "\\end{split}\n",
    "$$\n",
    "\n",
    "- 单向的，从左至右的，（BERT 的 B 表示的含义就是 bidirectional）\n",
    "\n",
    "- 具体的解码过程：\n",
    "    \n",
    "$$\n",
    "\\begin{split}\n",
    "&p(y_t=w_i|y_{\\lt t}, x)=\\text{softmax}(z_{t,i})\\\\\n",
    "&\\hat{\\textbf{y}}={\\arg\\max}_{\\textbf{y}}P(\\textbf{y}|\\textbf{x})\n",
    "\\end{split}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fd0fd12",
   "metadata": {},
   "source": [
    "## gpt2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ca8a439",
   "metadata": {},
   "source": [
    "|model        |参数量       |hidden dim        |  block 数量 | \n",
    "| ----------- |----------- | ---------------- | -----------| \n",
    "|gpt2         |124M        |    768  (64\\*12) |          12|\n",
    "|gpt2-medium  |355M        |    1024 (64\\*16) |          24|\n",
    "|gpt2-large   |774M        |    1280 (64\\*20) |          36|\n",
    "|gpt2-xl      |1.56B       |    1600 (64\\*25) |          48|"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "55bc258e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:06:06.932872Z",
     "start_time": "2023-05-04T14:06:06.563139Z"
    }
   },
   "outputs": [],
   "source": [
    "from transformers import AutoModelForCausalLM\n",
    "from transformers_utils import get_params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e5659eb1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:06:36.772442Z",
     "start_time": "2023-05-04T14:06:21.239203Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1,557,611,200\n"
     ]
    }
   ],
   "source": [
    "# 'gpt2', 'gpt2-medium', 'gpt2-large', 'gpt2-xl'\n",
    "# 'gpt2': https://huggingface.co/gpt2\n",
    "# 'gpt2-medium': https://huggingface.co/gpt2-medium\n",
    "# 'gpt2-large': https://huggingface.co/gpt2-large\n",
    "# 'gpt2-xl': https://huggingface.co/gpt2-xl\n",
    "# 没有 case/uncased 之分\n",
    "model_ckpt = 'gpt2-xl'\n",
    "config = AutoConfig.from_pretrained(model_ckpt)\n",
    "tokenizer = AutoTokenizer.from_pretrained(model_ckpt)\n",
    "model = AutoModel.from_pretrained(model_ckpt)\n",
    "# model_clm = AutoModelForCausalLM.from_pretrained(model_ckpt)\n",
    "print(format(get_params(model), ','))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "06ae831e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:07:04.936407Z",
     "start_time": "2023-05-04T14:07:04.930116Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPT2Config {\n",
       "  \"_name_or_path\": \"gpt2-xl\",\n",
       "  \"activation_function\": \"gelu_new\",\n",
       "  \"architectures\": [\n",
       "    \"GPT2LMHeadModel\"\n",
       "  ],\n",
       "  \"attn_pdrop\": 0.1,\n",
       "  \"bos_token_id\": 50256,\n",
       "  \"embd_pdrop\": 0.1,\n",
       "  \"eos_token_id\": 50256,\n",
       "  \"initializer_range\": 0.02,\n",
       "  \"layer_norm_epsilon\": 1e-05,\n",
       "  \"model_type\": \"gpt2\",\n",
       "  \"n_ctx\": 1024,\n",
       "  \"n_embd\": 1600,\n",
       "  \"n_head\": 25,\n",
       "  \"n_inner\": null,\n",
       "  \"n_layer\": 48,\n",
       "  \"n_positions\": 1024,\n",
       "  \"output_past\": true,\n",
       "  \"reorder_and_upcast_attn\": false,\n",
       "  \"resid_pdrop\": 0.1,\n",
       "  \"scale_attn_by_inverse_layer_idx\": false,\n",
       "  \"scale_attn_weights\": true,\n",
       "  \"summary_activation\": null,\n",
       "  \"summary_first_dropout\": 0.1,\n",
       "  \"summary_proj_to_labels\": true,\n",
       "  \"summary_type\": \"cls_index\",\n",
       "  \"summary_use_proj\": true,\n",
       "  \"task_specific_params\": {\n",
       "    \"text-generation\": {\n",
       "      \"do_sample\": true,\n",
       "      \"max_length\": 50\n",
       "    }\n",
       "  },\n",
       "  \"transformers_version\": \"4.28.1\",\n",
       "  \"use_cache\": true,\n",
       "  \"vocab_size\": 50257\n",
       "}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e8b3085e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:08:55.813850Z",
     "start_time": "2023-05-04T14:08:55.799103Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPT2Model(\n",
       "  (wte): Embedding(50257, 1600)\n",
       "  (wpe): Embedding(1024, 1600)\n",
       "  (drop): Dropout(p=0.1, inplace=False)\n",
       "  (h): ModuleList(\n",
       "    (0-47): 48 x GPT2Block(\n",
       "      (ln_1): LayerNorm((1600,), eps=1e-05, elementwise_affine=True)\n",
       "      (attn): GPT2Attention(\n",
       "        (c_attn): Conv1D()\n",
       "        (c_proj): Conv1D()\n",
       "        (attn_dropout): Dropout(p=0.1, inplace=False)\n",
       "        (resid_dropout): Dropout(p=0.1, inplace=False)\n",
       "      )\n",
       "      (ln_2): LayerNorm((1600,), eps=1e-05, elementwise_affine=True)\n",
       "      (mlp): GPT2MLP(\n",
       "        (c_fc): Conv1D()\n",
       "        (c_proj): Conv1D()\n",
       "        (act): NewGELUActivation()\n",
       "        (dropout): Dropout(p=0.1, inplace=False)\n",
       "      )\n",
       "    )\n",
       "  )\n",
       "  (ln_f): LayerNorm((1600,), eps=1e-05, elementwise_affine=True)\n",
       ")"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2c758bc",
   "metadata": {},
   "source": [
    "### tokenizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "87f5f2a3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:09:44.199858Z",
     "start_time": "2023-05-04T14:09:44.192162Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPT2TokenizerFast(name_or_path='gpt2-xl', vocab_size=50257, model_max_length=1024, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'bos_token': '<|endoftext|>', 'eos_token': '<|endoftext|>', 'unk_token': '<|endoftext|>'}, clean_up_tokenization_spaces=True)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1b792e2d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:12:49.510394Z",
     "start_time": "2023-05-04T14:12:49.499636Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'bos_token': '<|endoftext|>', 'eos_token': '<|endoftext|>', 'unk_token': '<|endoftext|>'}\n",
      "{'bos_token': '<|endoftext|>', 'eos_token': '<|endoftext|>', 'unk_token': '<|endoftext|>'}\n",
      "[50256]\n",
      "<|endoftext|>\n",
      "[220, 220]\n",
      " \n",
      "[15496]\n",
      "[31373]\n",
      "[23748]\n",
      " hello\n",
      "[23748]\n",
      "[220, 23748]\n",
      "[220, 220, 23748]\n"
     ]
    }
   ],
   "source": [
    "print(tokenizer.special_tokens_map)\n",
    "print(tokenizer.special_tokens_map_extended)\n",
    "\n",
    "print(tokenizer.encode('<|endoftext|>'))\n",
    "print(tokenizer.decode(50256))\n",
    "\n",
    "print(tokenizer.encode('  '))\n",
    "print(tokenizer.decode(220))\n",
    "\n",
    "# 大小写敏感\n",
    "print(tokenizer.encode('Hello'))\n",
    "print(tokenizer.encode('hello'))\n",
    "print(tokenizer.encode(' hello'))\n",
    "print(tokenizer.decode(23748))\n",
    "print(tokenizer.encode(' hello'))\n",
    "print(tokenizer.encode('  hello'))\n",
    "print(tokenizer.encode('   hello'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd5bf232",
   "metadata": {},
   "source": [
    "|Token ID\t|  String                          | \n",
    "|-----------|----------------------------------|\n",
    "|39177\t    | ItemThumbnailImage               |\n",
    "|30210\t    | guiActiveUnfocused               |\n",
    "|39755\t    | isSpecialOrderable               |\n",
    "|31576\t    | externalActionCode               |\n",
    "|39753\t    | quickShipAvailable               |\n",
    "|39757\t    | channelAvailability              |\n",
    "|36174\t    | RandomRedditorWithNo             |\n",
    "|30899\t    | cloneembedreportprint            |\n",
    "|40242\t    | BuyableInstoreAndOnline          |\n",
    "|30906\t    | rawdownloadcloneembedreportprint |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "895a5af4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:13:30.790485Z",
     "start_time": "2023-05-04T14:13:30.784405Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[39177]\n",
      "[30906]\n"
     ]
    }
   ],
   "source": [
    "print(tokenizer.encode('ItemThumbnailImage'))\n",
    "print(tokenizer.encode('rawdownloadcloneembedreportprint'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2cd8dca9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:13:47.136515Z",
     "start_time": "2023-05-04T14:13:47.127702Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'input_ids': [3666, 4004, 3124, 318, 8262, 260, 1904], 'attention_mask': [1, 1, 1, 1, 1, 1, 1]}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenizer('My favorite color is chartreuse')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3fc56fec",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:14:02.972310Z",
     "start_time": "2023-05-04T14:14:02.961885Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[8262, 260, 1904]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenizer.encode(' chartreuse')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ac8f7d3",
   "metadata": {},
   "source": [
    "### attention_mask"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0a05479",
   "metadata": {},
   "source": [
    "- 更好地构造结构化，批次化输入 (tensor, shape 是一定的)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7a42add6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:14:36.807841Z",
     "start_time": "2023-05-04T14:14:36.795146Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('../imgs/attention_mask.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d7ef4263",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:15:56.078303Z",
     "start_time": "2023-05-04T14:15:52.333767Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'input_ids': tensor([[1026,  481, 6290,  287,  262]]), 'attention_mask': tensor([[1, 1, 1, 1, 1]])}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from transformers import GPT2LMHeadModel, GPT2Tokenizer\n",
    "\n",
    "tokenizer = GPT2Tokenizer.from_pretrained('gpt2')\n",
    "gpt2 = GPT2LMHeadModel.from_pretrained('gpt2')\n",
    "\n",
    "context = tokenizer('It will rain in the', return_tensors='pt')\n",
    "context\n",
    "# prediction = gpt2.generate(**context, max_length=10)\n",
    "# tokenizer.decode(prediction[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e59289ca",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:17:42.620501Z",
     "start_time": "2023-05-04T14:17:42.610499Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[ 1026,   481,  6290,   287,   262, 50256, 50256, 50256],\n",
      "        [   40,   765,   284,  4483,   257,  1263,  9396,   286],\n",
      "        [ 3666,  3290,   318, 50256, 50256, 50256, 50256, 50256]])\n",
      "tensor([[1, 1, 1, 1, 1, 0, 0, 0],\n",
      "        [1, 1, 1, 1, 1, 1, 1, 1],\n",
      "        [1, 1, 1, 0, 0, 0, 0, 0]])\n"
     ]
    }
   ],
   "source": [
    "# tokenizer.padding_side = \"left\"\n",
    "tokenizer.padding_side = \"right\"\n",
    "tokenizer.pad_token = tokenizer.eos_token\n",
    "\n",
    "sentences = [\"It will rain in the\",\n",
    "            \"I want to eat a big bowl of\",\n",
    "            \"My dog is\"]\n",
    "inputs = tokenizer(sentences, return_tensors=\"pt\", padding=True)\n",
    "print(inputs.input_ids)\n",
    "print(inputs.attention_mask)\n",
    "# output_sequences = gpt2.generate(**inputs)\n",
    "\n",
    "# for seq in output_sequences:\n",
    "#     print(tokenizer.decode(seq))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "919ad739",
   "metadata": {},
   "source": [
    "## forward"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72dce0f0",
   "metadata": {},
   "source": [
    "- GPT2Model\n",
    "    - wte: word token embedding\n",
    "    - wpe: word position embedding\n",
    "- LMHead\n",
    "    - mlp: hidden_state => vocab_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "08e9fa43",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:19:27.873474Z",
     "start_time": "2023-05-04T14:18:56.448698Z"
    }
   },
   "outputs": [],
   "source": [
    "model_ckpt = 'gpt2-xl'\n",
    "config = AutoConfig.from_pretrained(model_ckpt)\n",
    "tokenizer = AutoTokenizer.from_pretrained(model_ckpt)\n",
    "model = AutoModel.from_pretrained(model_ckpt)\n",
    "model_clm = AutoModelForCausalLM.from_pretrained(model_ckpt).to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1afffd54",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:19:38.780994Z",
     "start_time": "2023-05-04T14:19:38.774604Z"
    },
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPT2Model(\n",
       "  (wte): Embedding(50257, 1600)\n",
       "  (wpe): Embedding(1024, 1600)\n",
       "  (drop): Dropout(p=0.1, inplace=False)\n",
       "  (h): ModuleList(\n",
       "    (0-47): 48 x GPT2Block(\n",
       "      (ln_1): LayerNorm((1600,), eps=1e-05, elementwise_affine=True)\n",
       "      (attn): GPT2Attention(\n",
       "        (c_attn): Conv1D()\n",
       "        (c_proj): Conv1D()\n",
       "        (attn_dropout): Dropout(p=0.1, inplace=False)\n",
       "        (resid_dropout): Dropout(p=0.1, inplace=False)\n",
       "      )\n",
       "      (ln_2): LayerNorm((1600,), eps=1e-05, elementwise_affine=True)\n",
       "      (mlp): GPT2MLP(\n",
       "        (c_fc): Conv1D()\n",
       "        (c_proj): Conv1D()\n",
       "        (act): NewGELUActivation()\n",
       "        (dropout): Dropout(p=0.1, inplace=False)\n",
       "      )\n",
       "    )\n",
       "  )\n",
       "  (ln_f): LayerNorm((1600,), eps=1e-05, elementwise_affine=True)\n",
       ")"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b0e5a948",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:19:49.653094Z",
     "start_time": "2023-05-04T14:19:49.643430Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPT2LMHeadModel(\n",
       "  (transformer): GPT2Model(\n",
       "    (wte): Embedding(50257, 1600)\n",
       "    (wpe): Embedding(1024, 1600)\n",
       "    (drop): Dropout(p=0.1, inplace=False)\n",
       "    (h): ModuleList(\n",
       "      (0-47): 48 x GPT2Block(\n",
       "        (ln_1): LayerNorm((1600,), eps=1e-05, elementwise_affine=True)\n",
       "        (attn): GPT2Attention(\n",
       "          (c_attn): Conv1D()\n",
       "          (c_proj): Conv1D()\n",
       "          (attn_dropout): Dropout(p=0.1, inplace=False)\n",
       "          (resid_dropout): Dropout(p=0.1, inplace=False)\n",
       "        )\n",
       "        (ln_2): LayerNorm((1600,), eps=1e-05, elementwise_affine=True)\n",
       "        (mlp): GPT2MLP(\n",
       "          (c_fc): Conv1D()\n",
       "          (c_proj): Conv1D()\n",
       "          (act): NewGELUActivation()\n",
       "          (dropout): Dropout(p=0.1, inplace=False)\n",
       "        )\n",
       "      )\n",
       "    )\n",
       "    (ln_f): LayerNorm((1600,), eps=1e-05, elementwise_affine=True)\n",
       "  )\n",
       "  (lm_head): Linear(in_features=1600, out_features=50257, bias=False)\n",
       ")"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_clm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4a7931bc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:20:32.917654Z",
     "start_time": "2023-05-04T14:20:32.906097Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'input_ids': tensor([[  32,  890,  890,  640, 2084]]), 'attention_mask': tensor([[1, 1, 1, 1, 1]])}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 大小写是不同的token，\n",
    "# 空格也是token\n",
    "input_txt = \"A long long time ago\"\n",
    "model_inputs = tokenizer(input_txt, return_tensors='pt')\n",
    "model_inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "3dcd53f5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:20:47.601155Z",
     "start_time": "2023-05-04T14:20:47.589238Z"
    }
   },
   "outputs": [],
   "source": [
    "input_ids = model_inputs['input_ids'].to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "2c886ce0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:21:41.022705Z",
     "start_time": "2023-05-04T14:21:40.926437Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 5, 50257])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([[[ 1.5445,  2.5812,  0.6197,  ..., -7.4777, -5.5282,  0.6108],\n",
       "         [ 1.0344,  1.5582, -2.5840,  ..., -6.3941, -2.5380, -1.0215],\n",
       "         [ 2.0070,  2.3330, -1.1671,  ..., -7.7938, -3.9385,  1.0949],\n",
       "         [ 5.6171,  4.4350, -2.1919,  ..., -7.9733, -5.2310,  1.6343],\n",
       "         [ 4.8450,  5.3529, -0.7294,  ..., -7.7071, -3.8473,  2.5437]]],\n",
       "       device='cuda:0', grad_fn=<UnsafeViewBackward0>)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output = model_clm(input_ids=input_ids)\n",
    "print(output.logits.shape)\n",
    "output.logits"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "748f876e",
   "metadata": {},
   "source": [
    "### model.transformer()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6860b9c0",
   "metadata": {},
   "source": [
    "`(transformer): GPT2Model`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b77de4ee",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:22:39.414998Z",
     "start_time": "2023-05-04T14:22:39.274954Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 5, 1600])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([[[-0.5478,  0.0327,  0.7691,  ..., -4.5986,  0.2638,  0.1780],\n",
       "         [-1.0570, -0.8408,  0.8223,  ..., -1.3309,  1.0921,  0.7939],\n",
       "         [-0.5805, -1.1760,  0.4954,  ..., -1.3462,  1.2957,  1.2741],\n",
       "         [-0.2789, -1.5347,  0.6579,  ..., -1.6087,  1.1029,  0.9785],\n",
       "         [ 0.2617,  0.0104,  0.6141,  ..., -1.6620,  1.4646,  0.6588]]],\n",
       "       device='cuda:0', grad_fn=<ViewBackward0>)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_clm.eval()\n",
    "print(model_clm.transformer(input_ids).last_hidden_state.shape)\n",
    "model_clm.transformer(input_ids).last_hidden_state"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b4c1425",
   "metadata": {},
   "source": [
    "### 自定义（model.transformer()）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "3ea43edf",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:23:53.115252Z",
     "start_time": "2023-05-04T14:23:53.105661Z"
    },
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPT2Config {\n",
       "  \"_name_or_path\": \"gpt2-xl\",\n",
       "  \"activation_function\": \"gelu_new\",\n",
       "  \"architectures\": [\n",
       "    \"GPT2LMHeadModel\"\n",
       "  ],\n",
       "  \"attn_pdrop\": 0.1,\n",
       "  \"bos_token_id\": 50256,\n",
       "  \"embd_pdrop\": 0.1,\n",
       "  \"eos_token_id\": 50256,\n",
       "  \"initializer_range\": 0.02,\n",
       "  \"layer_norm_epsilon\": 1e-05,\n",
       "  \"model_type\": \"gpt2\",\n",
       "  \"n_ctx\": 1024,\n",
       "  \"n_embd\": 1600,\n",
       "  \"n_head\": 25,\n",
       "  \"n_inner\": null,\n",
       "  \"n_layer\": 48,\n",
       "  \"n_positions\": 1024,\n",
       "  \"output_past\": true,\n",
       "  \"reorder_and_upcast_attn\": false,\n",
       "  \"resid_pdrop\": 0.1,\n",
       "  \"scale_attn_by_inverse_layer_idx\": false,\n",
       "  \"scale_attn_weights\": true,\n",
       "  \"summary_activation\": null,\n",
       "  \"summary_first_dropout\": 0.1,\n",
       "  \"summary_proj_to_labels\": true,\n",
       "  \"summary_type\": \"cls_index\",\n",
       "  \"summary_use_proj\": true,\n",
       "  \"task_specific_params\": {\n",
       "    \"text-generation\": {\n",
       "      \"do_sample\": true,\n",
       "      \"max_length\": 50\n",
       "    }\n",
       "  },\n",
       "  \"transformers_version\": \"4.28.1\",\n",
       "  \"use_cache\": true,\n",
       "  \"vocab_size\": 50257\n",
       "}"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "03b8a578",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:26:00.320576Z",
     "start_time": "2023-05-04T14:26:00.306571Z"
    }
   },
   "outputs": [],
   "source": [
    "def gpt2_transformer_forward(model, input_ids):\n",
    "    model.eval()\n",
    "    input_shape = input_ids.size()\n",
    "    input_ids = input_ids.view(-1, input_shape[-1])\n",
    "    batch_size = input_ids.shape[0]\n",
    "    \n",
    "    past_length = 0\n",
    "    past_key_values = tuple([None] * len(model.h))\n",
    "    position_ids = torch.arange(past_length, input_shape[-1] + past_length, dtype=torch.long, device=device)\n",
    "    position_ids = position_ids.unsqueeze(0).view(-1, input_shape[-1])\n",
    "    \n",
    "    encoder_attention_mask = None\n",
    "    \n",
    "    # embedding\n",
    "    inputs_embeds = model.wte(input_ids)\n",
    "    position_embeds = model.wpe(position_ids)\n",
    "    hidden_states = inputs_embeds + position_embeds\n",
    "    hidden_states = model.drop(hidden_states)\n",
    "    output_shape = input_shape + (hidden_states.size(-1),)\n",
    "    \n",
    "    head_mask = model.get_head_mask(None, model.config.n_layer)\n",
    "    \n",
    "    for i, (block, layer_past) in enumerate(zip(model.h, past_key_values)):\n",
    "        outputs = block(\n",
    "                    hidden_states,\n",
    "                    layer_past=layer_past,\n",
    "                    head_mask=head_mask[i],\n",
    "                )\n",
    "        hidden_states = outputs[0]\n",
    "    hidden_states = model.ln_f(hidden_states)\n",
    "    hidden_states = hidden_states.view(output_shape)\n",
    "    return hidden_states"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4fb8abbb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:26:12.090277Z",
     "start_time": "2023-05-04T14:26:11.994552Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[[-0.5478,  0.0327,  0.7691,  ..., -4.5986,  0.2638,  0.1780],\n",
      "         [-1.0570, -0.8408,  0.8223,  ..., -1.3309,  1.0921,  0.7939],\n",
      "         [-0.5805, -1.1760,  0.4954,  ..., -1.3462,  1.2957,  1.2741],\n",
      "         [-0.2789, -1.5347,  0.6579,  ..., -1.6087,  1.1029,  0.9785],\n",
      "         [ 0.2617,  0.0104,  0.6141,  ..., -1.6620,  1.4646,  0.6588]]],\n",
      "       device='cuda:0')\n"
     ]
    }
   ],
   "source": [
    "with torch.no_grad():\n",
    "    print(gpt2_transformer_forward(model_clm.transformer, input_ids))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f412c8b8",
   "metadata": {},
   "source": [
    "### lmhead_model(input_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "255a3cf7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:26:50.847102Z",
     "start_time": "2023-05-04T14:26:50.756422Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[[ 1.5445,  2.5812,  0.6197,  ..., -7.4777, -5.5282,  0.6108],\n",
       "         [ 1.0344,  1.5582, -2.5840,  ..., -6.3941, -2.5380, -1.0215],\n",
       "         [ 2.0070,  2.3330, -1.1671,  ..., -7.7938, -3.9385,  1.0949],\n",
       "         [ 5.6171,  4.4350, -2.1919,  ..., -7.9733, -5.2310,  1.6343],\n",
       "         [ 4.8450,  5.3529, -0.7294,  ..., -7.7071, -3.8473,  2.5437]]],\n",
       "       device='cuda:0', grad_fn=<UnsafeViewBackward0>)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_clm(input_ids=input_ids).logits"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0771c437",
   "metadata": {},
   "source": [
    "### 自定义 lmhead_model forward"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "f046fcfa",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:27:32.642540Z",
     "start_time": "2023-05-04T14:27:32.637622Z"
    }
   },
   "outputs": [],
   "source": [
    "def gpt2_clm_forward(model, input_ids):\n",
    "    model.eval()\n",
    "    transformer_outputs = model.transformer(input_ids)\n",
    "    hidden_states = transformer_outputs[0]\n",
    "    print(hidden_states.shape)\n",
    "    lm_logits = model.lm_head(hidden_states)\n",
    "    print(lm_logits.shape)\n",
    "    return lm_logits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "8732088e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-04T14:27:39.097058Z",
     "start_time": "2023-05-04T14:27:38.990995Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 5, 1600])\n",
      "torch.Size([1, 5, 50257])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([[[ 1.5445,  2.5812,  0.6197,  ..., -7.4777, -5.5282,  0.6108],\n",
       "         [ 1.0344,  1.5582, -2.5840,  ..., -6.3941, -2.5380, -1.0215],\n",
       "         [ 2.0070,  2.3330, -1.1671,  ..., -7.7938, -3.9385,  1.0949],\n",
       "         [ 5.6171,  4.4350, -2.1919,  ..., -7.9733, -5.2310,  1.6343],\n",
       "         [ 4.8450,  5.3529, -0.7294,  ..., -7.7071, -3.8473,  2.5437]]],\n",
       "       device='cuda:0', grad_fn=<UnsafeViewBackward0>)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpt2_clm_forward(model_clm, input_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6530c7a7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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